@article{1437694,
      recid = {1437694},
      author = {Zhang, Dengsheng,},
      title = {Fundamentals of image data mining : analysis, features,  classification and retrieval /},
      pages = {1 online resource :},
      abstract = {This unique and useful textbook presents a comprehensive  review of the essentials of image data mining, and the  latest cutting-edge techniques used in the field. The  coverage spans all aspects of image analysis and  understanding, offering deep insights into areas of feature  extraction, machine learning, and image retrieval. The  theoretical coverage is supported by practical mathematical  models and algorithms, utilizing data from real-world  examples and experiments. Topics and features: Describes  essential tools for image mining, covering Fourier  transforms, Gabor filters, and contemporary wavelet  transforms Develops many new exercises (most with MATLAB  code and instructions) Includes review summaries at the end  of each chapter Analyses state-of-the-art models,  algorithms, and procedures for image mining Integrates new  sections on pre-processing, discrete cosine transform, and  statistical inference and testing Demonstrates how features  like color, texture, and shape can be mined or extracted  for image representation Applies powerful classification  approaches: Bayesian classification, support vector  machines, neural networks, and decision trees Implements  imaging techniques for indexing, ranking, and presentation,  as well as database visualization This easy-to-follow,  award-winning book illuminates how concepts from  fundamental and advanced mathematics can be applied to  solve a broad range of image data mining problems  encountered by students and researchers of computer  science. Students of mathematics and other scientific  disciplines will also benefit from the applications and  solutions described in the text, together with the hands-on  exercises that enable the reader to gain first-hand  experience of computing.},
      url = {http://library.usi.edu/record/1437694},
      doi = {https://doi.org/10.1007/978-3-030-69251-3},
}